We propose a stochastic MPC scheme using an optimization over the initial state for predicted trajectory. Considering linear discrete-time systems under unbounded additive disturbances subject to chance constraints, we use constraint tightening based on probabilistic reachable sets design MPC. The avoids infeasibility issues arising from by including as decision variable. show that stabilizing ...

A two-player differential game of pollution control with uncertain initial disturbance stock is considered. In pace contemporary policy in the resource extraction industry, we initiate our research based on a model rehabilitation process which firms are required to compensate local rehabilitate polluted and dilapidated areas. Given reality that plays critical role production, cannot rigorously ...

This paper uses simulation studies to explore the behaviour of SCTP congestion control. Several possible variants of SCTP congestion control are identified and each is compared with the behaviour of Reno TCP, a well-known TCP variant. We identify three flaws in the current SCTP congestion control mechanisms. 1. Efficient recovery after a packet loss is only possible if SCTP generates the option...

This paper addresses the initial shift problem in iterative learning control with system relative degree. The tracking error caused by nonzero initial shift is detected when applying a conventional learning algorithm. Finite initial rectifying action is introduced in the learning algorithm and is shown e3ective in the improvement of tracking performance, in particular robustness with respect to...